Is Token Metadata Safe? — Trust Score: 55.4/100

What Is Token Metadata?

Token Metadata is a AI tool in the uncategorized category. ERC20 token metadata. Name, symbol, decimals, etc.

As of March 2026, Token Metadata is available on npm_full, making it an emerging tool in the AI ecosystem. But popularity alone does not equal safety — which is why Nerq independently analyzes every tool across 13+ trust signals.

How Nerq Assesses Token Metadata's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Token Metadata performs in each:

• Compliance (100/100): Token Metadata is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.

The overall Trust Score of 55.4/100 (D) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.

Who Should Use Token Metadata?

Token Metadata is designed for:

• Developers and teams working with uncategorized tools
• Organizations evaluating AI tools for their stack
• Researchers exploring AI capabilities in this domain

Risk guidance: Token Metadata is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.

How to Verify Token Metadata's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any AI tool:

1. Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Token Metadata's dependency tree.
3. Review permissions — Understand what access Token Metadata requires. AI tools should follow the principle of least privilege.
4. Test in isolation — Run Token Metadata in a sandboxed environment before granting access to production data or systems.
5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=@injectivelabs/token-metadata
6. Review the license — Confirm that Token Metadata's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
7. Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses security concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Token Metadata

When evaluating whether Token Metadata is safe, consider these category-specific risks:

Best Practices for Using Token Metadata Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Token Metadata while minimizing risk:

When Should You Avoid Token Metadata?

Even promising tools aren't right for every situation. Consider avoiding Token Metadata in these scenarios:

• Production environments handling sensitive customer data
• Regulated industries (healthcare, finance, government) without additional compliance review
• Mission-critical systems where downtime has significant business impact

For each scenario, evaluate whether Token Metadata's trust score of 55.4/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Token Metadata Compares to Industry Standards

Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Token Metadata's score of 55.4/100 is near the category average of 62/100.

This places Token Metadata in line with the typical uncategorized tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.

Trust Score History

Nerq continuously monitors Token Metadata and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or maintenance patterns change, Token Metadata's score is updated within 24 hours.

Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Token Metadata's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=@injectivelabs/token-metadata&include=history

Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Token Metadata are strengthening or weakening over time.

Key Takeaways

• Token Metadata has a Trust Score of 55.4/100 (D) and is not yet Nerq Verified.
• Token Metadata shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
• Among uncategorized tools, Token Metadata scores near the category average of 62/100, suggesting room for improvement relative to peers.
• Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.

Related Safety Checks